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Cognitive Limitations and Consumer Behavior

  • Numerous examples of behavior contradict the predictions of the standard rational choice model. People often fail to ignore sunk costs. They play tennis indoors when, by their own account, they would prefer to play outside. They behave differently when they lose a ticket than when they lose an equivalent amount of cash. Psychologists argue that such behavior is the result of limitations in human cognitive capacity. People use mental accounting systems that reduce the complexity of their decisions, sometimes at the expense of consistency with the axioms of rational choice.

  • An important class of departures from rational choice appears to result from the asymmetric value function described by Kahneman and Tversky. In contrast to the rational choice model, which uses a utility function defined on total wealth, Kahneman's and Tversky's descriptive theory uses a value function defined over changes in wealth. Unlike the traditional model, it gives losses much heavier decision weight than gains. This feature makes decisions extremely sensitive to how alternatives are framed. For example, if a loss is combined with a slightly larger gain, the net effect typically receives a positive evaluation, as it would under the rational choice model. But Kahneman and Tversky suggest that when gains and losses occur as discrete events, people tend to evaluate their effects separately, in which case the impact of the loss tends to outweigh that of the larger gain. A loss combined with a slightly larger gain produces a positive effect, whereas taken separately their net effect is negative.

  • Another source of suboptimal decisions is failure to anticipate how we will adapt to different consumption experiences over time. In choosing between two goods, people tend to favor the alternative that provides greater satisfaction at the moment of decision. Evidence suggests, however, that the satisfaction provided by some goods and activities tends to decay quickly over time, whereas for others it decays less quickly or even increases. The upshot is a tendency to spend too much on goods and activities in the former category, and too little on those in the latter.

  • Decisions under uncertainty also often violate the prescriptions of the expected utility model. Here, too, the asymmetric value function provides a consistent description of several important patterns. People tend to be risk averse in the domain of gains but risk seeking in the domain of losses. The result is that subtle differences in the framing of the problem can shift the mental reference point used for reckoning gains and losses, which, in turn, can produce radically different patterns of choice.

  • Another important departure from rational choice occurs in the heuristics, or rules of thumb, people use to make estimates of important decision factors. The availability heuristic says that one way people estimate the frequency of a given class of events is by the ease with which they can recall relevant examples. This leads to predictable biases because actual frequency is not the only factor that governs how easy it is to recall examples. People tend to overestimate the frequency of vivid or salient events, and of other events that are especially easy to retrieve from memory.

  • Another important heuristic is representativeness. People estimate the likelihood that an item belongs to a given class by how representative it is of that class. We saw that this often leads to substantial bias because representativeness is only one of many factors that govern this likelihood. Shyness may indeed be a trait representative of librarians, but because there are so many more salespeople than librarians, it is much more likely that a randomly chosen shy person is a salesperson than a librarian.

  • Anchoring and adjustment is a third heuristic that often leads to biased estimates of important decision factors. This heuristic says that people often make numerical estimates by first picking a convenient (but sometimes irrelevant) anchor and then adjusting from it (usually insufficiently) on the basis of other potentially relevant information. This procedure often causes people to underestimate the failure rate of projects with many steps. Such a project fails if any one of its essential elements fails, which means that even if the failure rate of each element is extremely low, a project with many elements is nonetheless very likely to fail. Because people tend to anchor on the failure rate for the typical step, and adjust insufficiently from it, they often grossly overestimate the likelihood of success. This may help explain the naive optimism of people who start new businesses.

  • Another departure from rational choice traces to the psychophysics of perception. Psychologists have discovered that the barely perceptible change in any stimulus is proportional to its initial level. This seems to hold true as well when the stimulus in question is the price of a good or service. People think nothing of driving across town to save $5 on a $25 radio, but would never dream of doing so to save $5 on a $1000 TV set.

  • Departures from rational choice may also occur because people simply have difficulty choosing between alternatives that are hard to compare. The rational choice model assumes that we have complete preference orderings, but in practice, it often seems to require a great deal of effort for us to decide how we feel about even very simple alternatives.

  • Finally, departures from rational choice may occur because people lack sufficient willpower to carry out plans they believe to be in their own interests. In such instances, people may try to place tempting, but inferior, alternatives out of reach.

  • Behavioral models of choice often do a much better job of predicting actual decisions than the rational choice model. It is important to remember, however, that the behavioral models claim no normative significance. That is, the mere fact that they predict, for example, that people often do ignore sunk costs should not be taken to mean that people should ignore them. The rational choice model says we can make better decisions by ignoring sunk costs, and most people, on reflection, strongly agree. In this respect, behavioral models of choice are an important tool for helping us avoid common pitfalls in decision making.

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